Parastoo Sadeghi

Australian National University, Canberra, Australian Capital Territory, Australia

Are you Parastoo Sadeghi?

Claim your profile

Publications (174)

  • Noman Akbar · Nan Yang · Parastoo Sadeghi · Rodney A. Kennedy
    [Show abstract] [Hide abstract] ABSTRACT: We propose a novel algorithm to design user load-achieving pilot sequences that mitigate pilot contamination in multi-cell massive multiple-input multiple-output (MIMO) networks. To this end, we first derive expressions for the user load and the load region of the network considering both small-scale and large-scale propagation effects. We then develop the pilot sequence algorithm for multi-cell massive MIMO networks as per the rules of generalized Welch bound equality design. Notably, we find that our algorithm and the corresponding downlink power allocation ensure that the user load is achieved when the signal-to-interference-plus-noise ratio (SINR) requirements for the users lie within the load region. Furthermore, we demonstrate the performance advantage of our proposed design relative to the existing designs, in terms of a larger load region and a higher maximum permitted SINR. Finally, we show that our proposed design can satisfy the pre-defined SINR requirements for users with a finite number of antennas at the base station (BS), while the existing designs cannot satisfy the same requirements even with an infinite number of antennas at the BS.
    Article · Jul 2016
  • Ni Ding · Chung Chan · Qiaoqiao Zhou · [...] · Parastoo Sadeghi
    [Show abstract] [Hide abstract] ABSTRACT: We propose a modified decomposition algorithm (MDA) to solve the asymptotic communication for omniscience (CO) problem where the communication rates could be real or fractional. By starting with a lower estimation of the minimum sum-rate, the MDA algorithm iteratively updates the estimation by the optimizer of a Dilworth truncation problem until the minimum is reached with a corresponding optimal rate vector. We also propose a fusion method implementation of the coordinate-wise saturation capacity algorithm (CoordSatCapFus) for solving the Dilworth truncation problem, where the minimization is done over a fused user set with a cardinality smaller than the original one. We show that the MDA algorithm is less complex than the existing ones. In addition, we show that the non-asymptotic CO problem, where the communication rates are integral, can be solved by one more call of the CoordSatCapfus algorithm. By choosing a proper linear ordering of the user indices in the MDA algorithm, the optimal rate vector is also the one with the minimum weighted sum-rate.
    Article · Jul 2016
  • Ni Ding · Chung Chan · Qiaoqiao Zhou · [...] · Parastoo Sadeghi
    Conference Paper · Jul 2016
  • Yousef N. Shnaiwer · Sameh Sorour · Parastoo Sadeghi · [...] · Tareq Y. Al-Naffouri
    [Show abstract] [Hide abstract] ABSTRACT: The femtocaching idea was proposed as a solution to compensate for the weak backhaul capacity, by deploying coverage-limited nodes with high storage capacity called femtocaches (FCs). In this paper, the macrocell offloading problem in femtocaching-assisted cellular networks is investigated. The objective is to minimize the number of transmissions by the macrocell base station (MBS) given that all requests should be served simultaneously to satisfy quality-of-experience (QoE) of the clients. We first formulate this MBS offloading problem as an optimization problem over a network coding graph, and show that it is NP-hard. Therefore, we propose an ONC-broadcast offloading scheme that exploits both broadcasting and opportunistic network coding (ONC) to minimize the number of required MBS transmissions. We utilize a random graph model to approximate the performance of the proposed ONC-broadcast scheme in terms of the resultant average number of transmissions by the MBS. Moreover, despite the complexity of finding the optimal solution for each and every case, we prove that this ONC-broadcast scheme is asymptotically optimal, i.e., for large number of requests, the ONC-broadcast scheme achieves a similar macrocell offloading performance to that of the optimal solution. To implement the ONC-broadcast scheme, we devise a heuristic that employs a dual conflict graph or broadcasting at the FCs such that the remaining requests can be served using the minimum number of transmissions at the MBS. Simulations show that the dual graph scheme improves MBS offloading as compared to the traditional separate graph scheme. Furthermore, the simple heuristic proposed to implement the ONC-broadcast scheme achieves a very close performance to the optimal ONC-broadcast scheme.
    Article · Jun 2016
  • Mohammad S. Karim · Ahmed Douik · Sameh Sorour · Parastoo Sadeghi
    Conference Paper · May 2016
  • Ni Ding · Parastoo Sadeghi · Rodney A. Kennedy
    [Show abstract] [Hide abstract] ABSTRACT: We study the adaptive modulation (AM) problem in a network-coded two-way relay channel (NC-TWRC), where each of the two users controls its own bit rate in the $m$-ary quadrature amplitude modulation ($m$-QAM) to minimize the transmission error rate and enhance the spectral efficiency. We show that there exists a strategic complementarity, one user tends to transmit while the other decides to do so in order to enhance the overall spectral efficiency, which is beyond the scope of the conventional single-agent AM scheduling method. We propose a two-player game model parameterized by the signal-to-noise ratios (SNRs) of two user-to-user channels and prove that it is a supermodular game where there always exist the extremal pure strategy Nash equilibria (PSNEs), the largest and smallest PSNEs. We show by simulation results that the extremal PSNEs incur a similar bit error rate (BER) as the conventional single-agent AM scheme, but significantly improve the spectral efficiency in the NC-TWRC system. The study also reveals the Pareto order of the extremal PSNEs: The largest and smallest PSNEs are Pareto worst and best PSNEs, respectively. Finally, we derive the sufficient conditions for the extremal PSNEs to be symmetric and monotonic in channel SNRs. We also discuss how to utilize the symmetry and monotonicity to relieve the complexity in the PSNE learning process.
    Article · May 2016
  • Parastoo Sadeghi · Fatemeh Arbabjolfaei · Young-Han Kim
    [Show abstract] [Hide abstract] ABSTRACT: In this paper, we study the capacity region of the general distributed index coding. In contrast to the traditional centralized index coding where a single server contains all $n$ messages requested by the receivers, in the distributed index coding there are $2^n-1$ servers, each containing a unique non-empty subset $J$ of the messages and each is connected to all receivers via a noiseless independent broadcast link with an arbitrary capacity $C_J \ge 0$. First, we generalize the existing polymatroidal outer bound on the capacity region of the centralized problem to the distributed case. Next, building upon the existing centralized composite coding scheme, we propose three distributed composite coding schemes and derive the corresponding inner bounds on the capacity region. We present a number of interesting numerical examples, which highlight the subtleties and challenges of dealing with the distributed index coding, even for very small problem sizes of $n=3$ and $n=4$.
    Article · Apr 2016
  • N. Aboutorab · P. Sadeghi
    [Show abstract] [Hide abstract] ABSTRACT: In this paper, we investigate the use of instantly decodable network coding (IDNC) for improving two fundamental performance metrics, namely, the completion time (as a measure of throughput) and mean decoding delay, in multicast cooperative data exchange (CDE) systems, where a group of geographically close clients cooperate with each other to obtain their missing packets. Here, an IDNC scheme is used for the transmissions across these clients. We utilize the stochastic shortest path (SSP) technique to study the minimum mean completion time problem. However, since finding the optimum solution is intractable, we use the obtained formulation to draw some theoretical guidelines to heuristically find solutions that can efficiently reduce the completion time. Second, we formulate the minimum mean decoding delay problem as selecting the appropriate maximal clique over well-structured graphs at the clients, and in order to reduce its complexity, we propose a simple heuristic algorithm for it. The effectiveness of our proposed algorithms is verified through extensive simulations and comparisons with existing techniques.
    Article · Mar 2016
  • Ni Ding · Chung Chan · Qiaoqiao Zhou · [...] · Parastoo Sadeghi
    [Show abstract] [Hide abstract] ABSTRACT: We consider the problem of how to fairly distribute the minimum sum-rate among the users in communication for omniscience (CO). We formulate a problem of minimizing a weighted quadratic function over a submodular base polyhedron which contains all achievable rate vectors, or transmission strategies, for CO that have the same sum-rate. By solving it, we can determine the rate vector that optimizes the Jain's fairness measure, a more commonly used fairness index than the Shapley value in communications engineering. We show that the optimizer is a lexicographically optimal (lex-optimal) base and can be determined by a decomposition algorithm (DA) that is based on submodular function minimization (SFM) algorithm and completes in strongly polynomial time. We prove that the lex-optimal minimum sum-rate strategy for CO can be determined by finding the lex-optimal base in each user subset in the fundamental partition and the complexity can be reduced accordingly.
    Article · Jan 2016
  • Ahmed Douik · Mohammad S. Karim · Parastoo Sadeghi · Sameh Sorour
    [Show abstract] [Hide abstract] ABSTRACT: Consider a radio access network wherein a base-station is required to deliver a set of order-constrained messages to a set of users over independent erasure channels. This paper studies the delivery time reduction problem using instantly decodable network coding (IDNC). Motivated by time-critical and order-constrained applications, the delivery time is defined, at each transmission, as the number of undelivered messages. The delivery time minimization problem being computationally intractable, most of the existing literature on IDNC propose sub-optimal online solutions. This paper suggests a novel method for solving the problem by introducing the delivery delay as a measure of distance to optimality. An expression characterizing the delivery time using the delivery delay is derived, allowing the approximation of the delivery time minimization problem by an optimization problem involving the delivery delay. The problem is, then, formulated as a maximum weight clique selection problem over the IDNC graph wherein the weight of each vertex reflects its corresponding user and message's delay. Simulation results suggest that the proposed solution achieves lower delivery and completion times as compared to the best-known heuristics for delivery time reduction.
    Article · Jan 2016
  • Source
    Shama N. Islam · Salman Durrani · Parastoo Sadeghi
    Full-text Conference Paper · Jan 2016
  • Chuling Huang · Parastoo Sadeghi · Ali A. Nasir
    Conference Paper · Jan 2016
  • Parastoo Sadeghi
    [Show abstract] [Hide abstract] ABSTRACT: Index coding is often studied with the assumption that a single source has all the messages requested by the receivers. We refer to this as \emph{centralized} index coding. In contrast, this paper focuses on \emph{distributed} index coding and addresses the following question: How does the availability of messages at distributed sources (storage nodes) affect the solutions and achievable rates of index coding? An extension to the work of Arbabjolfaei et al. in ISIT 2013 is presented when distributed sources communicate via a semi-deterministic multiple access channel (MAC) to simultaneous receivers. A numbers of examples are discussed that show the effect of message distribution and redundancy across the network on achievable rates of index coding and motivate future research on designing practical network storage codes that offer high index coding rates.
    Article · Dec 2015
  • Source
    Shama Naz Islam · Salman Durrani · Parastoo Sadeghi
    Full-text Article · Dec 2015 · Physical Communication
  • Source
    Shama N. Islam · Salman Durrani · Parastoo Sadeghi
    [Show abstract] [Hide abstract] ABSTRACT: In this paper, we consider a functional decode and forward (FDF) multi-way relay network (MWRN) where a common user facilitates each user in the network to obtain messages from all other users. We propose a novel user pairing scheme, which is based on the principle of selecting a common user with the best average channel gain. This allows the user with the best channel conditions to contribute to the overall system performance. Assuming lattice code based transmissions, we derive upper bounds on the average common rate capacity and the average sum rate with the proposed pairing scheme. Considering binary phase shift keying modulation as the simplest case of lattice code transmission, we derive asymptotic average bit error rate (BER) of the MWRN. We show that in terms of the achievable rates, the proposed pairing scheme outperforms the existing pairing schemes under a wide range of channel scenarios. The proposed pairing scheme also has lower average BER compared to existing schemes. We show that overall, the MWRN performance with the proposed pairing scheme is more robust, compared to existing pairing schemes, especially under worst case channel conditions when majority of users have poor average channel gains.
    Full-text Article · Dec 2015 · Physical Communication
  • Conference Paper · Dec 2015
  • Noman Akbar · Nan Yang · Parastoo Sadeghi · Rodney A. Kennedy
    [Show abstract] [Hide abstract] ABSTRACT: We propose a novel pilot sequence design to mitigate pilot contamination in multi-cell multiuser massive multiple-input multiple-output networks. Our proposed design generates pilot sequences for all users in the multi-cell network and devises power allocation at base stations (BSs) for downlink transmission. The pilot sequences together with the power allocation ensure that the user capacity of the network is achieved and the predefined signal-to-interference-plus-noise ratio (SINR) requirements of all users are met. To realize our design, we first derive new closed-form expressions for the user capacity and the capacity region of the network. Built upon these expressions, we then develop a new algorithm to obtain the required pilot sequences and power allocation. We further determine the minimum number of antennas required at BSs to achieve certain SINR requirements of all users. Numerical results are presented to corroborate our analysis and to explicitly examine the impact of key parameters, such as the pilot sequence length and the total number of users, on the network performance. A pivotal conclusion is reached that our design achieves a larger capacity region, supports a more diverse range of SINR requirements, and needs a lower number of antennas at BSs to fulfill the predefined SINR requirements than the existing designs.
    Article · Nov 2015
  • Ni Ding · Chung Chan · Tie Liu · [...] · Parastoo Sadeghi
    [Show abstract] [Hide abstract] ABSTRACT: We propose a coalition game model for the problem of communication for omniscience (CO). In this game model, the core contains all achievable rate vectors for CO with sum-rate being equal to a given value. Any rate vector in the core distributes the sum-rate among users in a way that makes all users willing to cooperate in CO. We give the necessary and sufficient condition for the core to be nonempty. Based on this condition, we derive the expression of the minimum sum-rate for CO and show that this expression is consistent with the results in multivariate mutual information (MMI) and coded cooperative data exchange (CCDE). We prove that the coalition game model is convex if the sum-rate is no less than the minimal value. In this case, the core is non-empty and a rate vector in the core that allocates the sum-rate among the users in a fair manner can be found by calculating the Shapley value.
    Article · Oct 2015
  • Mohammad S. Karim · Sameh Sorour · Parastoo Sadeghi
    [Show abstract] [Hide abstract] ABSTRACT: In this paper, we study the problem of distributing a real-time video sequence to a group of partially connected cooperative wireless devices using instantly decodable network coding (IDNC). In such a scenario, the coding conflicts occur to service multiple devices with an immediately decodable packet and the transmission conflicts occur from simultaneous transmissions of multiple devices. To avoid these conflicts, we introduce a novel IDNC graph that represents all feasible coding and transmission conflict-free decisions in one unified framework. Moreover, a real-time video sequence has a hard deadline and unequal importance of video packets. Using these video characteristics and the new IDNC graph, we formulate the problem of minimizing the mean video distortion before the deadline as a finite horizon Markov decision process (MDP) problem. However, the backward induction algorithm that finds the optimal policy of the MDP formulation has high modelling and computational complexities. To reduce these complexities, we further design a two-stage maximal independent set selection algorithm, which can efficiently reduce the mean video distortion before the deadline. Simulation results over a real video sequence show that our proposed IDNC algorithms improve the received video quality compared to the existing IDNC algorithms.
    Article · Aug 2015
  • Source
    Ni Ding · Parastoo Sadeghi · Rodney A. Kennedy
    [Show abstract] [Hide abstract] ABSTRACT: This paper considers a cross-layer adaptive modulation system that is modeled as a Markov decision process (MDP). We study how to utilize the monotonicity of the optimal transmission policy to relieve the computational complexity of dynamic programming (DP). In this system, a scheduler controls the bit rate of the m-quadrature amplitude modulation (m-QAM) in order to minimize the long-term losses incurred by the queue overflow in the data link layer and the transmission power consumption in the physical layer. The work is done in two steps. Firstly, we observe the L-natural-convexity and submodularity of DP to prove that the optimal policy is always nondecreasing in queue occupancy/state and derive the sufficient condition for it to be nondecreasing in both queue and channel states. We also show that, due to the L-natural-convexity of DP, the variation of the optimal policy in queue state is restricted by a bounded marginal effect: The increment of the optimal policy between adjacent queue states is no greater than one. Secondly, we use the monotonicity results to present two low complexity algorithms: monotonic policy iteration (MPI) based on L-natural-convexity and discrete simultaneous perturbation stochastic approximation (DSPSA). We run experiments to show that the time complexity of MPI based on L-natural-convexity is much lower than that of DP and the conventional MPI that is based on submodularity and DSPSA is able to adaptively track the optimal policy when the system parameters change.
    Full-text Article · Aug 2015 · IEEE Transactions on Communications